The hidden talent gaps slowing down ERP upgrades and AI implementations

Article

By Angela Lurie, Executive Director, Robert Half Management Resources, and Ryan M. Sutton, Executive Director, Technology, Robert Half

Chief financial officers (CFOs), Chief information officers (CIOs) and other finance and tech leaders are under pressure to modernize systems, strengthen controls and improve insight. They are also expected to deliver transformation with minimal disruption to everyday business operations. But executing change at scale isn’t easy, and even the most well-funded ERP and AI implementations can easily get delayed or face unexpected roadblocks or challenges.

Project bottlenecks often arise due to the constraints of technical debt and the inflexibility of legacy systems. In many cases, there is also a people problem to contend with. These complex projects require professionals who can translate business needs into clean data, improved processes, coordinated decisions, rigorous testing and sustained change support. Those capabilities are in short supply in today’s labor market, and they’re difficult to keep dedicated to programs that can run 12 to 24 months or longer.

The result is a familiar pattern of early momentum, followed by delays and rework once the real demands of migration, design and testing collide with operational reality. Four hidden talent gaps, in particular, tend to drive slowdowns in ERP and AI projects. Here’s a closer look at what they are, why they create problems, and how finance and technology leaders can overcome them.

4 talent gaps that undermine ERP and AI investments

The data readiness gap
The process ownership gap
The cross-functional coordination gap
The technical expertise and capacity gap

The data readiness gap

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Most finance and tech leaders know data will be one of the most challenging aspects of implementing AI tools or upgrading an ERP system, not to mention getting the most value from those efforts. What often comes as a surprise, though, is the scale and persistence of effort required to get data implementation-ready, and how hard it is to resource that work effectively.

Over time, charts of accounts expand to accommodate growth, acquisitions and reorganizations. Vendor and customer records accumulate inconsistencies. Even core definitions—like what constitutes an “entity,” “project” or “department”—can vary across the business. And while much of the organization’s information now sits inside large data warehouses, the underlying issues remain: data structures don’t align, cleanliness and integrity are uneven, and accessibility is limited. Meanwhile, legacy systems were never designed to feed consistent, AI‑ready analytics, making it even harder to unlock value from the information leaders already have.

Responsibility for addressing these issues is often unclear. Finance understands how the data is used but may lack the capacity to profile, cleanse and validate it at the scale and speed the implementation requires. IT understands the systems but may not have the context to resolve ambiguity. Meanwhile, the professionals who know the data best are often the same people responsible for the financial close, reporting and business support, and therefore have little or no time to devote to data readiness efforts.

As a result, data issues are acknowledged but resolution is deferred—until migration testing fails or AI outputs don’t align with expectations. At that point, data cleanup becomes urgent and reactive, pulling experienced talent away from both the implementation project and day-to-day operations.

Sustained ownership is the answer here. Clean, reliable data requires people with deep functional understanding who can stay focused on profiling, cleansing and validation for as long as the program demands. However, in today’s tight labor market, securing that combination of expertise, availability and continuity is increasingly difficult without dedicated—and often temporary—support.

What skills are in high demand, and what are employers’ strategic priorities in the first half of 2026? Read Robert Half’s Demand for Skilled Talent report to find out.

The process ownership gap

ERP and AI tools promise standardization and automation, but they depend on clear, well-understood processes to support consistent work, dependable information and decisions teams can trust.

Many organizations don’t fully appreciate how fragmented their workflows are until future-state design begins. Tasks that appear straightforward on paper are often performed differently across teams or regions. Documentation may be incomplete or outdated. Workarounds have evolved under the radar to compensate for system limitations or staffing changes. In many cases, critical knowledge resides with a handful of long-tenured employees whose schedules are already full.

This is why process ownership is essential to ERP or AI implementation success. It means having named leaders for each core process who understand the work end to end, can make design decisions, and have the time to stay engaged throughout the program. Without that sustained involvement, design discussions slow down, decisions get revisited and compromises are made to keep the project moving—even if they preserve unnecessary complexity. Worse, there is also the risk of embedding today’s inefficiencies into tomorrow’s systems.

True process ownership requires authority, context and time. Yet the individuals best suited for these roles are often high-performing managers or senior contributors who are already essential to daily operations. Unless they’re deliberately supported—through backfills, temporary analysts or role redesign—process ownership becomes a secondary responsibility, and the implementation timeline stretches accordingly.

Explore more best practices for ERP transformation projects.

The cross-functional coordination gap

Another gap that can delay or even derail ERP and AI projects is a lack of cross-functional coordination. These initiatives extend far beyond finance. IT, HR, procurement, operations and sales can all influence how data is structured, how approvals flow and how performance is measured. Coordination across these groups is essential, yet difficult to sustain over long programs.

Early in a project, alignment often feels manageable. But as design progresses, dependencies multiply. Decisions made in one area have implications elsewhere. Small disconnects, like conflicting requirements, unclear decision rights or assumptions about integrations, can ripple outward and surface weeks or months later as delays or rework.

Effective alignment typically requires dedicated program leadership and cross-functional decision-makers who are empowered to make timely decisions when priorities conflict and dependencies collide. However, keeping the right decision-makers engaged at the same time, over the full life of the program, is a challenge. Leaders rotate in and out of workshops. Priorities shift. And without consistent coordination, teams end up solving the same problems more than once.

See these tips for building a high-performing ERP project team.

The technical expertise and capacity gap

ERP and AI implementations bring periods of concentrated work, often tied to immovable deadlines, that extend well beyond daily operations. Configuration, integration design, reporting development, testing, training and change enablement all require specialized skills and sustained attention. However, most finance teams operate with little excess capacity.

Asking the same people to manage close cycles, audits and business support while also executing a major transformation creates cumulative strain. Over time, that strain shows up as delayed testing, uneven change management and even employee burnout.

Another reality: Many of the skills required during implementation are highly specialized and not needed at full scale once the new system stabilizes. Deep ERP functional expertise, data engineering for migration, large-scale UAT support and platform-specific change management are essential during the program, yet inefficient to staff permanently.

This creates a practical dilemma for finance leaders. Permanent hiring may not make sense, but relying solely on internal teams creates risk. Short-term may help, but it may not be enough. What’s required instead is access to specialized talent that can stay engaged for as long as the work demands—whether that’s months or multiple phases over several years.

What high-performing teams do differently

Now that we’ve outlined the gaps, let’s consider solutions for closing them. CFOs and finance leaders whose organizations deliver ERP and AI implementations with fewer delays take a more intentional approach to talent. In practice, they consistently do 3 things differently:

1. They assess capacity and capability before the program begins

These leaders identify where internal stakeholders and subject matter experts can realistically engage and where additional support will be required—especially for data readiness, process ownership and cross-functional decision-making. Rather than assuming teams can absorb transformation work indefinitely, they plan for the additional workload and skill requirements from the start.

2. They align talent to each phase of the implementation

Instead of front-loading resources and assuming internal teams can carry the rest, leaders deliberately match talent to each phase—design, migration, testing, go-live and stabilization. This preserves continuity as demands shift, keeps critical expertise in place when it’s needed most, and reduces disruption and the risk of delays as the program moves from build to adoption.

3. They embrace a blended talent model

Internal teams can provide institutional knowledge and long-term ownership. Interim leaders, project specialists and technical experts—working on a contract basis or through consulting engagements—can bring focused expertise and execution capacity. Backfills protect core operations. Together, this mix of talent allows organizations to move at the pace ERP, AI and other modernization and transformation projects require without sacrificing control or undermining morale.

Learn what to expect when using consulting and talent solutions for ERP projects.

Talent strategy: The difference between implementation and lasting impact

AI adoption and the use of modern ERP platforms can transform how finance teams operate. They enable a shift away from manual tasks and processes toward more standardized, automated and insight-driven workflows built on cleaner, more reliable data that supports better decision making.

The talent gaps that can slow ERP and AI initiatives aren’t signs of weak teams or poor planning. They are structural challenges created by the scope, pace and complexity of modern finance transformation, and by the need to execute large-scale change while day-to-day operations continue. They also require a level of specialized expertise and sustained focus that extends beyond what most finance teams can absorb alongside their core responsibilities.

When talent strategy is treated with the same rigor as system selection and design, ERP and AI investments are far more likely to deliver on their promise—and to do so without overwhelming the teams responsible for making them work. Finance leaders who recognize this early—and secure the right mix of resources for the duration of the work—can position their organizations to move faster, reduce risk and realize value sooner.

Needs support for your ERP or AI implementation project in 2026?

Robert Half and global consulting firm Protiviti, a Robert Half subsidiary, offer flexible engagement models—advisory, workstream delivery and resource augmentation—that allow us to tailor support to your specific needs at every phase of your project.

Protiviti’s world-class consulting capabilities combined with Robert Half’s expansive network of specialized talent can help your business accelerate timelines, control costs, manage change and realize greater value from your ERP and AI investments.

You can learn more about our solutions and resources here. And when you’re ready to move forward with your ERP upgrade or AI initiative, contact us to tell us about your project needs.

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